Constraining Atmospheric Selenium Emissions Using Observations, Global Modeling, and Bayesian Inference.
Journal
Environmental science & technology
ISSN: 1520-5851
Titre abrégé: Environ Sci Technol
Pays: United States
ID NLM: 0213155
Informations de publication
Date de publication:
16 06 2020
16 06 2020
Historique:
pubmed:
14
5
2020
medline:
10
10
2020
entrez:
14
5
2020
Statut:
ppublish
Résumé
Selenium (Se) is an essential dietary element for humans and animals, and the atmosphere is an important source of Se to soils. However, estimates of global atmospheric Se fluxes are highly uncertain. To constrain these uncertainties, we use a global model of atmospheric Se cycling and a database of more than 600 sites where Se in aerosol has been measured. Applying Bayesian inference techniques, we determine the probability distributions of global Se emissions from the four major sources: anthropogenic activities, volcanoes, marine biosphere, and terrestrial biosphere. Between 29 and 36 Gg of Se are emitted to the atmosphere every year, doubling previous estimates of emissions. Using emission parameters optimized by aerosol network measurements, our model shows good agreement with the aerosol Se observations (
Identifiants
pubmed: 32401017
doi: 10.1021/acs.est.0c01408
pmc: PMC7301612
doi:
Substances chimiques
Aerosols
0
Selenium
H6241UJ22B
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
7146-7155Références
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